Tag: 10 Week Semester (page 1 of 2)

As technology continues to change the way we experience sectors of our daily life, it’s not surprising that cyber-security risk and vulnerabilities are also on the rise. From popular fitness tracking apps to university data systems, there have been dozens of high profile security breaches in the first half of 2018 alone.

According to Trustwave, $600 billion is lost to cyber-crime globally every year. In 2016, 53% percent of IT security professionals felt more pressured to secure their organizations than in 2015, demonstrating a growing need for information security management of businesses, government agencies, and other enterprises. Now more than ever, companies need leaders who can establish teams, processes and policies to secure their data.

Brandeis GPS offers a course in Information Security Management that explores security concepts, infrastructures, standards, protocols, and best practices. that are necessary for today’s information security professionals. The course focuses on management and governance, assessing and communicating risk, law (compliance) and ethics, policies, planning (strategy and operations), contingency planning (disaster recovery and incident response), and testing. These concepts are applied and discussed in the context of common enterprise scenarios.

Throughout the course, students acquire an understanding of the fundamentals of information assurance solutions and learn to establish a comprehensive security strategy and execution plan. By the end of the session, students will be able to apply the concepts, principles, and vocabulary of IT and information security within the context of their own organizations.

Information Security Management is a fully online, 10-week course that will next run in October 2018.

At Brandeis GPS, you can take up to two courses before enrolling in one of our 12 online Master’s degree programs. If you’re interested in exploring the MS in Information Security Leadership, or would like to learn more about information security management as part of your own professional development, contact the GPS office for more information or to request a syllabus: 781-736-8787, gps@brandeis.edu, or submit your information.

The health care industry has always been at the center of emerging technology as a leader in the research and application of advanced sciences. Now, more than ever, the industry is on the edge of an innovation boom. Health care information technology possesses vast potential for advancement, making the field fertile ground for game-changing innovation and the next great frontier for big data.

The use of electronic health records (EHR), electronic prescribing, and digital imaging by health care providers has exploded in recent years, Health Affairsreports and the global health information exchange (HIE) market is projected to grow nearly ten percent per year, reaching $878 million in 2018, according to Healthcare Informatics.

But despite massive growth, health care IT faces a number of barriers slowing advancement.

When it comes to health information technologies, demand is outpacing delivery. Users desire higher levels of performance beyond the capacity of current IT solutions.

One reason technology is lagging is health care IT systems are independently developed and operated. Rather than one massive network, there are numerous “small shops developing unique products at high cost with no one achieving significant economies of scale or scope,” Health Affairs reported. As a result, innovations are isolated, progress is siloed, and technology cannot meaningfully advance.

To deliver the highest quality of care, the health care community must unite disparate systems in a centralized database. But, this is easier said than done. The industry must be sure to maintain the highest standards of security complying with Health Insurance Portability and Accountability Act of 1996 (HIPAA).

As a result, the health care IT industry currently faces a crucial challenge: devise an overarching system that guarantees security, sustainability, and scale.

“The growing role of information technology within health-care delivery has created the need to deepen the pool of informaticians who can help organizations maximize the effectiveness of their investment in information technology—and in so doing maximize impact on safety, quality, effectiveness, and efficiency of care,” the American Medical Informatics Association noted. The future of health care hinges on the ability to connect the big data dots and apply insights to a creating and practicing a smart IT strategy.

Organizations have thrown themselves into the big data trenches to innovate solutions to the problem facing their industry. Ninety-five percent of healthcare CEOs said they were exploring better ways to harness and manage big data, a PricewaterhouseCoopers study reported. With the commitment of the health care community, plus the right talent and resources, industry-advancing innovations won’t be far behind.

Health care is indisputably the next great frontier for big data. How we seek, receive, and pay for health care is poised to fundamentally change and health care informaticians will be leading the evolution.

“I always knew I would have to go back to school. My father presented a perfect example of that—nearing the end of his career, he had been unable to advance any further in his field because he lacked a four-year degree. For my generation, I equate that to not
having a graduate degree. Not wanting to be held back from a promotion, going back to school seemed a necessary evil; however, it was a terrifying thought. Travelling to classes, giving up nights and weekends, simply finding the time to work on assignments—there was no way I would be able to do all that. Then a co-worker told me about Brandeis GPS, and all my fears went away.

Online Learning made it all possible for me. I bought my first home about the same time I started my Program and Project Management degree; due to the nature of the program, I was able to balance the challenges of purchasing a home while keeping up with studies. Also thanks to online learning, I was able to take vacations during semesters! On ski trips to the western US with friends each year, I started every day with a couple hours of school work (and gallons of coffee) before hitting the slopes. I also remember a trip to Italy for a family wedding that coincided with Professional Communication. Had I been enrolled in a traditional classroom-based program, I may not have been able to make the trip; instead, I was posting discussion responses while riding the Rome to Florence train, using the onboard wireless, all while traveling at 250 kilometers per hour! Grazie Brandeis! Finally, in the last couple semesters, I was able to attend classes while training for an Ironman triathlon (as much as twenty hours of training per week) while also managing to not get fired from my job!

Graduate school does not have to be a life-consuming event, nor should it be. There is much to be enjoyed in life, such as home-ownership, vacations, and the pursuit of personal goals. These opportunities absolutely can occur, even while maintaining a career and a family. Not having to sacrifice other opportunities meant everything to me (and also meant the courses flew by in no time!). Brandeis GPS was and is the key to this ever-important balance of life and learning. Having achieved this milestone, I can now start
looking forward in my career, confident that I have the educational qualifications to support my endeavors. ”

Obvious, or oblivious? Short-term predictions eventually tend to make us look like one or the other—as Art Coviello astutely noted in making his own predictions for the security industry in 2014—depending on how they actually turn out. (Long-term predictions, however, which require an entirely different level of thinking, are evaluated against a different scale. For example, check out the many uncannily accurate predictions Isaac Asimov made for the 2014 World’s Fair, from his reflections on the just-concluded 1964 World’s Fair.)

Art’s short-term prediction about mobile malware:

2014 is the tipping point year of mobile malware: As businesses provide greater mobile access to critical business applications and sensitive data, and consumers increasingly adopt mobile banking, it is easy to see that mobile malware will rapidly grow in sophistication and ubiquity in 2014. We’ve already seen a strong uptick in both over the past few months and expect that this is just the beginning of a huge wave. We will see some high-profile mobile breaches before companies and consumers realize the risk and take appropriate steps to mitigate it. Interestingly, the Economist recently featured an article suggesting such fears were overblown. It is probably a good idea to be ready just the same.

The Economist article Art references (which is based on an earlier blog) asserts that “surprisingly little malware has found its way into handsets. . . smartphones have turned out to be much tougher to infect than laptops and desktop PCs.” (Ironically, the Economist also publishes vendor-sponsored content such as How Mobile Risks Are Pushing Companies Towards Better Security. I suppose that’s one way to beat the obvious or oblivious game: Place a bet on both sides.)

But the legitimate question remains: What is the risk of malware on mobile? Let’s focus here on enterprise risks, and set aside the consumer risks that Art also raised as a topic for another blog.

Keep in mind the proper definition of “risk”—one of the root causes of miscommunication among security professionals today, as I have noted in a previous blog—which is “the likelihood that a vulnerability will be exploited, and the corresponding business impact.” If we’re not talking about probabilities and magnitudes, we’re not talking about risk.

Regarding the probability of malware infecting mobile devices:

The Economist‘s article builds on findings from an academic paper published by researchers from Georgia Tech, along with a recent PhD student who is now the Chief Scientist at spin-off security vendor Damballa. Their core hypothesis is that the activities of such malware—including propagation and update of malicious code, command and control communications with infected devices, and transmission of stolen data—will be discernible in network traffic.

From three months of analysis, they found that about 3,500 mobile devices (out of a population of 380 million) were infected—roughly 0.001%, or 1 in 100,000.

Compare this to the computers cleaned per mille (CCM) metric regularly reported by Microsoft: For every 1,000 computers scanned by the Microsoft Malicious Software Removal Tool, CCM is the number of computers that needed to be cleaned after they were scanned. For 1H2012, the infection rates per 1,000 computers with no endpoint protection was between 11.6 and 13.6 per month.

All of this nets out to say that currently, mobile endpoints are three orders of magnitude less likely to be infected by malware than traditional endpoints.

But doesn’t this conflict with other published research about mobile malware? For example, I’ve previously blogged about an analysis of 13,500 free applications for Android devices, published in October 2012 by university researchers in Germany:

Of 100 apps selected for manual audit and analysis, 41 were vulnerable to man-in-the-middle (MITM) attacks due to various forms of SSL misuse.

Among the apps with confirmed vulnerabilities against MITM attacks, the cumulative installed base is up to 185 million users.

In another blog, I’ve noted that mobile applications have a more complex attack surface than traditional web applications—in addition to server-side code, they also deal with client-side code and (multiple) network channels. The impact of these threats is often multiplied, as in the common case of support for functions that were previously server-only (e.g., offline access). This makes security for mobile apps even more difficult for developers to address—mobile technology is not as well known, development teams are not as well educated, and testing teams are harder to keep current.

Meanwhile, malware on mobile is indeed becoming more prevalent: Currently over 350,000 instances from 300 malware families. It is also becoming more sophisticated—e.g., by obfuscating code to evade static and dynamic analysis, establishing device administration privileges to install additional code, and spreading code using Bluetooth, according to the IBM X-Force 2013 Mid-Year Trend and Risk Report.

But threats, vulnerabilities, and exploits are not risks. What would be obvious to predict is this: The likelihood of exploits based on mobile malware will increase dramatically in 2014—point Art.

The other half of the risk equation is the business impact of mobile exploits. From the enterprise perspective, we would have to estimate the cost of exploits such as compromise of sensitive corporate data, surveillance of key employees, and impersonation of key corporate identities—e.g., as part of attacks aimed at social networks or cloud platforms, where the mobile exploits are the means to a much bigger and more lucrative end. It seems quite reasonable to predict that we’ll see some high-profile, high-impact breaches along these lines in 2014—again, point Art.

Obvious or oblivious, you can put me down squarely with Art’s prediction for this one, with the exception that I would say the risk of mobile malware is much more concentrated and targeted than the all users/all devices scenario he seems to suggest.

As team leaders, we evaluate our team members and expect them to do the job up to our standards. Sometimes our standards are out of sync with their ability or training. After all, these individuals have not traveled in the same shoes as we have and may not have the skills or cognitive preparation to achieve what we expect. Therefore coaching becomes an integral part of helping teams grow to the next level.

In my experience, the most effective leaders shine when they are helping others day in and day out. This is where coaching enters the picture. Those team leaders who are really performing up to their capability (in a leadership capacity) are consistently coaching their colleagues (and not trying to micro-manage their activities). Individuals don’t appreciate being managed. But, they are more open to coaching if the coach immediately establishes his or her desire to help the individual meet their established goals.

The first and most important coaching skill is to be in the moment, not distracted by six different things on your mind. Coaching is about respect for each other. There is no more predictable way to show lack of respect as not being “present” or “engaged” during a conversation. I once had a boss whose eyes would become “fish eyes” during our conversations. Do you think I was being heard? Do you think I respected him?

Secondly, a good coach (team leader) will seek to understand by asking open-ended, empowering questions. It is very difficult to understand what is going on in someone else’s head if we ask simple yes/no questions. Questions need to be open-ended so we fully understand the complexity of an individual’s state of mind.

A third critical skill is the need for the coach to suspend judgment and remain reflective and objective. Being contemplative shows that you understand the thoughts or feelings in the conversation. These first three skills will help develop understanding, balance, and respect—all very important ingredients in a successful coaching relationship.

The fourth critical skill is affirming the conversation. This action brings into focus the individual’s desire to move ahead, whether it’s an improvement in performance or learning new skills and growing as a professional or human being.
These skills, when practiced and used daily, will help you become the most effective leader imaginable.

“I was very nervous taking an online course let alone pursuing my Master degree in a 100% virtual environment. The first day I opened Latte I was full of anxiety and overwhelmed because this was so new to me. This feeling of anxiety was quickly removed as I read through the professors instructions and read the responses from my fellow classmates, I was not in this alone and I had a community of people who were willing to help me out. This community of fellow classmates set the tone for the amazing experience I would have as I moved through the GPS program.

The strength in this program is the experience of the Professors, I was impressed with their knowledge in the course they were teaching and they were willing to share that knowledge with us to help us improve and build on the course material and apply it to our personal and professional life experiences.

The material was relevant and dealt with current issues we face with virtual teams, how to communicate and negotiate with them, how to manage projects and the software that we are using now, and organizational and operational strategies.

Finally, I don’t know what I would have done without my student advisor, Janice Steinberg, who kept in touch with me, answered me promptly every time I had a question (and I had a lot of questions), and was a great support system. The Brandeis GPS program has forever changed my life and I am very grateful that I was able to be a part of such an incredible and wonderful program and community of people.”

Emerging technologies have unlocked access to massive amounts of data, data that is mounting faster than organizations can process it. Buried under this avalanche of analytics are precious nuggets of information that organizations need to succeed. Companies can use these key insights to optimize efficiency, improve customer service, discover new revenue sources, and more. Those who can bridge the gap between data and business strategy will lead in our new economy.

Big Data’s potential impact on enterprises and industries as a whole is boundless. This potential is already being realized here in the Hub. Boston has been ahead of the curve when it comes to Big Data, thanks to our unique innovation ecosystem or our “Big Data DNA,” the Massachusetts Technology Leadership Council says. As a result, Boston is home to an especially high concentration of Big Data startups, but also powerhouse industries that have strategically leveraged analytics and transformed the space.

Check out how data and analytics has changed these five Boston industries.

These analytics have enabled marketers to access a more comprehensive report of campaign performances and in-depth view of buyer personas. Armed with these insights, marketers are able to refine their campaigns, improve forecasts, and advance their overall strategy.

Big Data also enables targeted marketing, a crucial component of today’s online strategy. You know those eerily accurate advertisements on your Facebook page? You can thank Big Data for that.

Analytics have unlocked enormous potential for marketers to better create, execute, and forecast campaigns. As a result, Boston has boomed with organizations entirely devoted to providing data-driven marketing solutions. HubSpot and Jumptap have emerged as leaders in this space, raising about $2.5 billion combined. Attivio, Visible Measures, DataXu are also leading marketing solutions providers.

Big Data’s impact can be seen first and foremost with the electronic health record. Big Data has launched the electronic health record into the twenty-first century, revolutionizing patient care, and empowering the success of companies like athenahealth based in Watertown.

“The meaningful use of electronic health records is key to ensuring that healthcare focuses on the needs of the patient, is delivered in a coordinated manner, and yields positive health outcomes at the lowest possible cost,” the report said.

The space has expanded even more since Massachusetts passed legislation requiring all providers to adopt electronic health records and connect to the health information exchange, Mass HIway in 2012.

The Shared Health Research Informatics Network (SHRINE) is another local innovation linking five hospitals (Beth Israel Deaconess Medical Center, Children’s Hospital Boston, Brigham and Women’s, Massachusetts General Hospital and the Dana Farber Cancer Center) in a centralized database to improve efficiency and quality of care.

After genomic data and patient data from electronic medical records, medical devices like pacemakers or a Fitbit, for example, are the fastest-growing sources of healthcare data. All of these rich sources of information can – and are – being leveraged by Boston healthcare providers to improve care and lower costs.

3. Government

The State of Massachusetts and the City of Boston lead the nation with a sophisticated public sector approach to data and analytics. Governor Patrick made Big Data part of policy, launching Massachusetts Big Data Initiative and supporting Mass Open Cloud Initiative, a public cloud that utilizes an innovative open and customizable model. In 2009, the Commonwealth launched the “the Open Data Initiative” inviting the public to access the government’s data library from nearly every department.

But analytics’ impact on the public sector is only beginning. Big Data can significantly improve the quality and efficiency of city services, and do so at a lower cost. But most importantly, data will unlock the future of urban living. Imagine if we knew the location of every bus, train, car, and bike in real-time? Imagine if we knew the profiles of every city building? This is the vision of Boston’s future as a “connected city” outlined in Mass Technology Leadership Council’s 2014 report Big Data & Connected Cities.

“Boston is making great strides in using technology to improve how city services are delivered but we can and will do more,” said Boston Mayor Marty Walsh about MassTLC’s report. “We are making vast amounts of the city’s big data available online to the public to not only increase transparency but to also spur innovation.”

Walsh has shown support for a data-driven, connected city and plans to hire a City of Boston Chief Digital Officer to help make this vision a reality.

4. Energy

Big Data is a big reason Boston has evolved as a leader in the energy industry. Tapping into Big Data yields much more comprehensive, accurate reports of energy usage and also illuminates how these building can operate more efficiently. As a result, the industry has boomed with companies helping buildings go green to save green, including local leaders EnerNoc, Retroficiency, and NextStepLiving. Buildings in Boston and beyond are being constructed or retrofitted with building automation systems – cloud-based, centralized control centers – which collect massive amounts of data, report on energy consumption in real-time, and can continually adjust building performance for optimum efficiency. This “smart” living is the wave of the future and entirely driven by Big Data.

5. Financial Services

Financial services is the fifth largest vertical for Big Data in Massachusetts. Big Data has made it possible to analyze financial data sets that previously weren’t accessible. Financial analysts now can examine and interpret unprecedented amounts of information and do so in new and innovative ways. For example, stock traders can collect and mine mass amounts of social media information to gauge public sentiment about products or companies, Information Week said.

Brandeis developed the program, which will be offered online, in response to the growing need for professionals highly skilled in the development of digital learning resources to support the rapid proliferation of online education courses and e-Learning powered training programs.

The Advisory Board reports that the demand for graduates with instructional design skills has increased in recent years, with a 63 percent increase in total job postings from 2010 to 2013, and a 50 percent increase in job postings for instructional designers and technologists. They also found that employers increasingly demand instructional designers with content development and collaboration skills.

“As public and private interest and money flow into this space, the need for highly trained professionals versed in the art and science of instructional design has almost certainly never been higher,” said Jason Gorman, a member of the professional advisory board for Brandeis’ master of science in online instructional design and technology program and vice president of learning experience design services at Six Red Marbles, the largest US-based development house for learning materials.

The Brandeis program will prepare students to harness educational technologies in the development of online courseware, use iterative and formative course development processes, and apply evidence-based learning methodologies to the design of dynamic online learning courses.

The program includes courses focusing on how to effectively apply various instructional design methodologies and principles of learning science to online course development, as well as courses focusing on the creative utilization of instructional technologies such as learning management systems and rich interactive courseware authoring tools. The program is designed to help instructional designers, educational technologists, and training and development specialists to successfully manage instructional design projects, work effectively with subject matter experts, apply evidence-based course design principles, and develop dynamic learning content to support fully-online course and program design and delivery.

Six core courses and four electives are required (a total of 30 graduate credits). Students may enroll in up to two courses before officially applying for admission.

“Instructional design has become a crucial skill set for both educational institutions and training and development organizations across a variety of industries and sectors,” said Brian Salerno, who chairs the new program. “The Internet and mobile platforms have emerged as a desirable delivery medium for learning and training materials, as well as educational courses. Instructional designers help organizations not just transition their learning content online, but help them to design effective online courses that harness all the advantages that instructional technology has to offer.”

Program graduates will be able to:

Apply evidence-based learning science and online pedagogical principles to the design, development, facilitation, and assessment of online courses and programs.

Evaluate and integrate instructional technologies, platforms, and collaborative tools for use in diverse instructional settings and applications.

Demonstrate creativity and innovation in the application of instructional design principles and technologies to respond to instructional challenges and emerging trends.

Lead and manage online instructional design and technology teams and projects, utilizing effective written and oral communication strategies.

This is the eighth part-time, online master degree program offered by Brandeis’ division of Graduate Professional Studies. The programs are geared for professionals looking to advance in their fields and keep up-to-date on the latest practices. Students are taught techniques that they can apply immediately in their places of work. The course instructors bring their applied experiences into the online classrooms, and the programs’ professional advisory boards help ensure that the courses and programs remain current and relevant.

Back when I was a manager inside organizations, I had many days that looked like this:

Meetings at 9am, 10am, 11am.

Working meeting through lunch (noon-1pm)

Meetings at 1pm, 2pm, 3pm.

I finally got a chance to check my email at 4pm. That’s when I discovered the world had blown up earlier in the day! (This is before cell phones. Yes, there was a time before cell phones.)

I then ran around like a chicken with my head cut off until I left work at 5:30pm, because, yes, I had a family, and, yes, I had to leave at 5:30pm. I either made dinner or picked up children, depending on my agreement with Mark.

We did the family stuff until 8pm, and when the kids went to sleep, I went back to work.

No wonder I was exhausted. My decision-making sometimes suffered, too. No surprise there.

Luckily, I had some days that did not look like this. I could solve the problems I encountered. And, some of these meetings were problem-solving meetings.

However, I had jobs where my senior managers did not manage their project portfolios, and we had many crises du jour. My VP would try to catch me on the way to my next meeting, and attempt to get me to “commit” to when a patch would be available or when we would start, or finish a project.

I swear, one of my VP’s used to know when I went to the ladies’ room. He did yell at me through the door, just as in this management myth.

This management myth is something I see often in organizations. This one is the one where people are running around so often they don’t actually solve problems.

Many problems are a combination of several problems. You might have to separate the problems and attack them in sequence. But, you might have to see the whole first, because there might be delays. The overarching problem is this: if you don’t give yourself enough time as a problem solving team, you can’t tell what the problem is. If you can’t tell what the problem is, you can’t solve it.

Problem solving tends to go through the process of:

Problem definition: What do we think the problem is?

Problem discussion: Let’s get all the divergent ideas on the table. Brainstorm, whatever we need to do.

Select a solution: Converge on a solution, trying out the ideas, understanding the results of each potential solution

Determine an action plan, with dates and people’s names associated with each step

Your problem solving might vary from this a bit, but that’s the general idea.

If you never give yourself enough time to solve problems because you’re always running around, how can you solve problems? It’s a problem. (Like the recursion there?)

That’s this month’s management myth, I Can Concentrate on the Run. Maybe your myth is that you can concentrate in a 10-minute standup. Maybe your myth is that you can concentrate on your drive into work. You might be able to, for some problems. Complex management problems require more than one person to solve them. They require more than a few minutes thought.

How do you solve complex problems in your organization? Do the problems run around the organization for a while? Or, do you solve them?

Today a client asked me to add an “average of averages” figure to some of his performance reports. I freely admit that a nervous and audible groan escaped my lips as I felt myself at risk of tumbling helplessly into the fifth dimension of “Simpson’s Paradox”– that is, the somewhat confusing statement that averaging the averages of different populations produces the average of the combined population. (I encourage you to hang in and keep reading, because ignoring this concept is an all too common and serious hazard of reporting data, and you absolutely need to understand and steer clear of it!)

Imagine that we’re analyzing data for several different physicians in a group. We establish a relation or correlation for each doctor to some outcome of interest (patient mortality, morbidity, client satisfaction). Simpson’s Paradox states that when we combine all of the doctors and their results, and look at the data in aggregate form, we may discover that the relation established by our previous research has reversed itself. Sometimes this results from some lurking variable(s) that we haven’t considered. Sometimes, it may be due simply to the numerical values of the data.

First, the “lurking variable” scenario. Imagine we are analyzing the following data for two surgeons:

Surgeon A operated on 100 patients; 95 survived (95% survival rate).

Surgeon B operated on 80 patients; 72 survived (90% survival rate).

At first glance, it would appear that Surgeon A has a better survival rate — but do these figures really provide an accurate representation of each doctor’s performance?

Deeper analysis reveals the following: of the 100 procedures performed by Surgeon A,

50 were classified as high-risk; 47 of those patients survived (94% survival rate)

When we include the lurking classification variable (high-risk versus routine surgeries), the results are remarkably transformed.

Now we can see that Surgeon A has a much higher survival rate in the high-risk category (94% v. 80%), while Surgeon B has a better survival rate in the routine category (100% v. 96%).

Let’s consider the second scenario, where numerical values can change results.

First, imagine that every month, the results of a patient satisfaction survey are exactly the same (Table 1).

The Table shows that calculating an average of each month’s result produces the same result (90%) as calculating a Weighted Average (90%). This congruence exists because each month, the denominator and numerator are exactly the same, contributing equally to the results.

Now consider Table 2, which also displays the number of responses received from a monthly patient-satisfaction survey, but where the number of responses and the number of patients who report being satisfied differ from month to month. In this case, taking an average of each month’s percentage allows some months to contribute to or affect the final result more than others. Here, for example, we are led to believe that 70% of patients are satisfied.

All results should in fact be treated as the data-set of interest, where the denominator is Total Responses (2,565) and the numerator is Total Satisfied (1,650). This approach correctly accounts for the fact that there is a different number of values each month, weights them equally, and produces a correct satisfaction rate of 64%. That is quite a difference from our previous answer of 6% — almost 145 patients!

How we calculate averages really does matter if we are committed to understanding our data and reporting it correctly. It matters if we want to identify opportunities to improve, and are committed to taking action.

As a final thought about averages, here is a wryly amusing bit of wisdom on the topic that also has the virtue of being concise. “No matter how long he lives, a man never becomes as wise as the average woman of 48.” -H. L. Mencken.